The Reseach Of The Grain Moisture Online Detection Technique Based On The Wide Frequency Excitation

Grain security has always been the focal point concerning the country's political, economic and social stability. Grain security includes quantity security, storage security, quality safety, eating security and other aspects. Among the many factors that affect grain security, the most important one is moisture. In the storage process, mildewing and worm-eaten of grain may easily happen if the moisture is too high. In grain processing, the physical properties, technological quality and food safety can be affected if the moisture is too high or too low. Therefore, the measurement of grain moisture on-line in the grain storing and processing is very necessary.This topic is one engineering application sub-topic of the "the study of Grain Moisture On-line Fuzzy Control Device" which is the key scientific and technological project of Science and Technology Department of Henan Province. In this paper, the change regularity of complex electrical parameters of wheat is studied in the broadband excitation (10KHz ~ 1MHz), a method of grain moisture on-line measurement is explored based on complex impedance theory, and an experimental device for grain moisture on-line detection is developed.The main works are as follows:1. The method of grain moisture measure is used based on complex impedance theory, and the grain moisture on-line measurement sensor is studied and produced.2. In the laboratory environment, the grain moisture on-line measurement system whose core is 16-bit microcontroller (MC9S12DG128) is established, and its hardware and software designing is completed.3. Based on the self-developed grain moisture on-line measurement device, the change regularity of complex electrical parameters (impedance module |Z|) of grain is studied in the broadband excitation, the sensitive frequency bands of food moisture is determined, and the drive signal frequency of the grain moisture on-line measure device is determined.4. Using BP Neural Network and MATLAB software, the data processing of two parameters (impedance module and temperature which are detected by the grain moisture on-line measure device), is investigated, so a solid foundation is lied for improving the device's performance.